The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
As the volume of information flowing on the web continues to increase, the need for automated tools that can assist users in receiving information valuable to them also increases. The information overload created by multitude of information sources, such as websites and social media sites, makes it difficult for users to know what piece of information is more suitable, relevant, or appropriate to their needs and desires. Also, a substantial portion of users' web surfing time is spent on separating information from noise.
In particular, service providers are continually challenged to deliver value and convenience to users by, for example, providing efficient search engine with high precision and low recall. One area of interest has been the development of finding and accessing desired content or search results. Currently, users locate content by forging through lengthy and exhausting search results, many of which include similar information. However, such methods can be time consuming and troublesome, especially if users are not exactly sure what they are looking for. Although these issues exist with respect to non-mobile devices, such issues are amplified when it comes to finding desired content or search results using mobile devices that have much limited screen space and can only display few search results per screen.
An opportunity arises to shift the burden of information filtering from users to automated systems and methods that determine contextual similarity between news feed items and present a single news feed item that represents a group of contextually similar news feed items. Improved user experience and engagement and higher user satisfaction and retention may result.